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HP HPE2-B08 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Supporting HPE Private Cloud AI Solutions | 20% | - Describe support resources and documentation - Describe capacity planning and optimization best practices - Identify how to perform firmware and software updates - Explain how to work with HPE support services |
| Installing and Configuring HPE Private Cloud AI Solutions | 30% | - Identify how to access and use HPE Private Cloud AI management interfaces - Explain how to deploy and configure HPE Private Cloud AI components - Describe the prerequisites for installing HPE Private Cloud AI - Describe how to validate the HPE Private Cloud AI installation - Identify the steps to configure the HPE Private Cloud AI environment |
| Architecting HPE Private Cloud AI Solutions | 20% | - Describe how HPE Private Cloud AI supports AI/ML workloads - Explain the HPE Private Cloud AI sizing and configuration guidelines - Identify components of the HPE Private Cloud AI architecture - Explain common AI use cases and how they map to workloads - Describe the AI/ML lifecycle and data pipeline requirements |
| Managing and Operating HPE Private Cloud AI Solutions | 30% | - Identify troubleshooting procedures and common issues - Explain how to monitor HPE Private Cloud AI performance and health - Explain backup and recovery procedures - Describe the tools and methods for managing HPE Private Cloud AI - Describe how to manage users and access control - Identify how to manage storage and data resources |
HPE Private Cloud AI Solutions Sample Questions:
An architect uses the HPE Intelligent Configurator for a customer with 120 concurrent users for a text generation task with RAG. The tool recommends a "Medium - Expanded (4-node)" configuration. The customer then reveals they want to use a smaller, more efficient 7B parameter model instead of the 13B model the tool defaulted to.
How will this change in model size likely affect the sizing tool's recommendation?
- A. It will upgrade the recommendation to a "Large - Standard (4-node)" configuration.
- B. It will have no effect, as the number of users is the primary factor.
- C. It will require the architect to switch to the "application capacity" sizing method.
- D. It will downgrade the recommendation to a "Medium - Standard (2-node)" configuration.
Correct Answer: D 🗳️
An architect is meeting with a prospective customer to determine the right HPE AI solution. The customer provides the following information about their situation.
```
- AI Status: No formal AI strategy. One successful PoC for theft prevention using computer vision is running at a single store.
- Goal: Wants to explore creating a "digital twin" of their supply chain for simulation, but has no clear KPIs.
- Team: Two data scientists, one ML engineer.
- Infrastructure: Ad-hoc use of public cloud for the PoC; no standardized tech stack.
```
Based on this profile, which AI maturity level and corresponding HPE solution should the architect initially position? (Choose 2.)
- A. The customer is a 'Deployer of AI at scale'.
- B. The customer is an 'AI Pro'.
- C. Lead with HPE Cray systems for the digital twin simulation.
- D. The customer is an 'Early AI user'.
- E. Lead with HPE Private Cloud AI with NVIDIA.
Correct Answer: D,E 🗳️
What is the primary advantage of using a Smart Template in OCA for HPE Private Cloud AI versus manually configuring a similar set of hardware?
- A. The Smart Template allows the use of components from other vendors.
- B. The Smart Template ensures all necessary and validated components, including specific cables, power cords, and software SKUs, are included correctly.
- C. The Smart Template guarantees the lowest possible price for the hardware.
- D. The Smart Template provides a 90-day free trial of the entire solution.
Correct Answer: B 🗳️
An architect is working with a customer who has been identified as an 'AI Pro'. They have a mature AI practice and are looking to scale their efforts in creating 'digital twin' simulations for automotive prototypes. This involves complex, graphics-intensive AI workloads. The customer wants a full-stack, turnkey private cloud solution to accelerate this initiative.
What is the most appropriate HPE solution to position for this customer?
- A. An HPE AI Services - Transformation Workshop to redefine their goals.
- B. A custom solution built on individual HPE ProLiant servers.
- C. HPE Private Cloud AI with NVIDIA.
- D. A set of AI-optimized HPE ProLiant DL servers for edge deployment.
Correct Answer: C 🗳️
A customer is expanding their HPE Private Cloud AI "Medium" configuration to support a new generative AI inferencing workload. They are concerned about network congestion and latency, as the AI workload is known to generate large, sudden bursts of traffic between the compute nodes and the storage system.
The solution uses NVIDIA Spectrum SN4700M switches for the AI interconnect.
Which feature of these switches is specifically designed to handle bursty traffic and prevent packet loss in a lossless Ethernet fabric?
- A. A fully shared buffer architecture that can dynamically absorb traffic bursts from any port.
- B. Support for Fibre Channel over Ethernet (FCoE) encapsulation.
- C. Integrated Silicon Root of Trust to validate the switch firmware integrity.
- D. The ability to route traffic based on application-layer metadata.
Correct Answer: A 🗳️




